Hi!
I am comparing high and low scores of stress levels. Can there be "unequal" sample sizes in conducting independent samples t-test?
I have N=160 on low stress levels ; and N=230 on high stress levels.
Thanks in advance
Yes. The unequal sample sizes does not bother the independent samples t-test.
In applying t test, it is not necessary to have equal size samples. Wish you luck.
Yes, it is possible to conduct an independent samples t-test with unequal sample sizes.
When conducting an independent samples t-test with unequal sample sizes, the test statistic will be calculated based on a weighted average of the sample means, where the weights are proportional to the sample sizes. This means that the larger sample size will have a greater influence on the test statistic than the smaller sample size.
It is important to note that the assumption of equal variances between the two groups must be tested and met in order to use the standard independent samples t-test. If the assumption of equal variances is violated, then a modified version of the t-test, such as the Welch's t-test, should be used instead.
In your case, with N=160 in the low stress group and N=230 in the high stress group, you can conduct an independent samples t-test to compare the means of the two groups, as long as the assumption of equal variances is met (or the Welch's t-test is used if the assumption of equal variances is violated).
Yes, there can be unequal sample sizes in group comparisons. It is quite common to have unequal sample sizes in group comparisons, particularly in observational studies or when studying rare diseases or events.
However, unequal sample sizes can affect the statistical power of the study and the precision of the estimates. Generally, having larger sample sizes in each group can improve the precision and statistical power of the study, but this is not always the case. Sometimes, having a smaller sample size in one group can lead to higher precision and power if that group has a larger effect size.
In practice, when conducting group comparisons with unequal sample sizes, researchers often use statistical tests that take into account the sample sizes, such as t-tests or ANOVA with unequal variances, or non-parametric tests such as the Mann-Whitney U test or Kruskal-Wallis test. They may also use techniques such as bootstrapping or permutation tests to account for the unequal sample sizes.
It's important to note that regardless of the sample size, it's always important to consider the assumptions and limitations of the statistical methods being used and to carefully interpret the results in the context of the study design and research question.
Yes, and the statistical power will be determined by the smallest sample size group.
With the n's you have, you should do a normality test to assess the behavior of the quantitative variables and determine whether to use parametric or nonparametric tests.
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